PGDA – Physics Guided Data Analysis

We therefore propose a collaborative research and development project seeking to develop physics guided machine learning by leveraging new collaborations in physics and data science at SDU, and through collaboration and exchange of know-how with a number of business partners. The project has 3 goals:

1) Develop the framework for physics guided data analysis, aiming for the ability to ingest data from multiple sensor sources, normalizing data using a common taxonomy and preparing data for processing using ML.

2) Develop the framework for a physics guided ML analytics system, capable of processing normalized sensor data to provide large scale ML driven anomaly detection and provide interpretable, actionable data and tangible insights.

3) Serve as a feasibility study for a joint large scale (DKK 50-100 mio.) and national research and development project, entailing the development of a physics guided ML analytics system based on platforms and sensors deployed in the Arctic region

The purpose of the national research and development project is the development of a physics guided and ML based data analytics system, the integration of a number of remote sensors and the deployment on a dual-use Medium Altitude Long Endurance (MALE class) UAV in the Arctic area.